Search Results - (machine OR machinery) learning (algorithms OR algorithm)
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Machine Learning Algorithms for Diabetes Prediction: A Review Paper
Published 2023“…Computer aided diagnosis; Data mining; Learning systems; Patient treatment; Predictive analytics; Robotics; Support vector machines; Data mining algorithm; Diabetes mellitus; Early diagnosis; Knowledge accumulation; Literature reviews; Prediction techniques; Review papers; Support vector machine algorithm; Learning algorithms…”
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…The application of artificial intelligence techniques (e.g., machine learning and deep learning) in medical science is becoming increasingly important for intelligently transforming all available information into valuable knowledge. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…As a result, this paper presents several machine learning algorithms that include Decision Tree (DT), Support Vector Machine (SVM), Extremely Fast Decision Tree (EFDT) and Hybrid (DT-SVM) for detecting and classifying conflicting flows in SDNs. …”
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Comparative analysis of machine learning algorithms for rainfall prediction in Kuantan, Pahang, Malaysia
Published 2025“…The analysis shows that the SVR consistently outperforms the other machine learning algorithms, achieving the lowest Mean Absolute Error (MAE) and Mean Squared Error (MSE).…”
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A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification
Published 2015“…The idea of developing FAM-OELM is motivated by the ELM concept proposed by Huang et al., for being an efficient learning algorithm that provides better generalization performance at a much faster learning speed. …”
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Machine learning classifications of multiple organ failures in a malaysian intensive care unit
Published 2024“…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”
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Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying
Published 2019“…However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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Development of machine learning-based algorithm to determine the condition in transformer oil
Published 2021“…This paper aims to develop a model for taking into consideration the results obtained from DGA to investigate the condition of transformer oil fault. Machine Learning (ML) algorithm have been utilized to detect the fault more accurate. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…The Windows malware dataset has been trained and tested by these three machine learning algorithms to get the percentage detection accuracy. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions
Published 2024Subjects: “…machine learning algorithms…”
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Propose a New Machine Learning Algorithm based on Cancer Diagnosis
Published 2018“…There are many machine learning algorithms proposed for multi-category classification problems in the cancer diagnosis area. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…In a semiconductor industry, wafer defect detection has becoming ubiquitous. Various machine learning algorithms had been adopted to be the “brain” behind the machine for reliable, fast defect detection. …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023“…Barium compounds; Cybersecurity; Data mining; Decision trees; Evolutionary algorithms; K-means clustering; Learning algorithms; Malware; Network security; Sodium compounds; Support vector machines; 'current; Comparatives studies; Cyber security; K-means; Machine learning algorithms; Malware attacks; Malware detection; Metaheuristic; Recent researches; Systematic literature review; Nearest neighbor search…”
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Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms
Published 2019“…Hence, the mapping of oil palm distributions via machine learning algorithm was better than that via non-machine learning algorithm.…”
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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Monograph -
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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